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Predictive Analytics For Commodity Prices
Make accurate predictions through big data analytics.
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Our Services

consulting
Consulting

Regardless of your unique requirements, we're happy to listen and consult.

Regardless of your unique requirements, we're happy to listen and consult.

market analysis
Market Analysis

We keep keep our eyes closely on the market to be updated of the latest trends.

We keep our eyes closely on the market to ensure we stay updated of the latest trends and news.

predictive analytics
Predictive Analysis

We'll build accurate and robust models to help you achieve your portfolio goals.

We'll test and build accurate and robust models to help you achieve your portfolio goals.

recommendations
Recommendations

Through industry experience and predictive models, we offer actionable recommendations.

With our industry experience and prediction results, we'll offer you actionable recommendations.

Commodities make the world go around.
Yet prices are highly volatile.

 

This makes supply and purchase agreements inherently risky. Past price forecasts were often hit-or-miss. They relied on general trends, together with fundamental analysis ‘feeling’ and technical analysis of price charts. Results were often undependable.

 

Now, new technologies of big data collection and management with big data analytics allow forecasts to be significantly more accurate. Tivlon Technologies brings together detailed commodity market knowledge and deep big data analytics expertise. We help you see further into the short and medium-term future and make decisions based on analytics, not just opinion.

Our Analytics Framework

How We Address Our Case Studies & Problem Statements

analytics approach

The fundamental goal of data analytics is to transform data from its unstructured, raw form into clear, meaningful information and actionable insights. Tivlon Technologies adopts the above data analytics approach by turning data into meaningful actions for our clients.

1. Descriptive

Making sense of the data by identifying patterns and relationships through the use of descriptive charts and tables. This helps us to have a clear understanding of what are the past trends and events that have happened.

2. Diagnosis

Making inference and hypothesis on why certain trends and fluctuations happened - by correlating it with past events and news to aid us in the selection of the right variables and factors that influences commodity prices.

3. Predictive

Development of predictive models to forecast future commodities price fluctuations. Through iterations and model refinement, we attempt to build the most robust and accurate models to help our clients make the most of their investments.

4. Prescriptive

Data analytics is of little value if it does not provide business users with actionable recommendations. We break down complex analysis by offering our clients with actionable recommendations to improve their investment decisions.

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Make Accurate and Meaningful Predictions

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